Trade policies and development in Africa: The Doha ...

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Trade policies and development in Africa: The Doha Development Agenda, the EU EPAs and ECOWAS A paper submitted for the Eleventh Annual Conference "Future of Global Economy" Helsinki, Finland By Charles K.D. Adjasi1 & Emmanuel Kinful Abstract This paper uses applied general equilibrium modelling under GTAP with the standard closure assumptions and labour market modifications to examine the likely outcome of two trade policy scenarios EPA and DDA and a third policy option-technological change in the ECOWAS region of Sub Saharan Africa. Simulation results show that with the exception of the EU and Ghana, the rest of ECOWAS suffers GDP and welfare losses arising mainly from adverse terms of trade effects of the EPAs. The DDA equally makes the ECOWAS region worse off in terms of GDP and welfare. We notice however that the ECOWAS gains substantially from improvements in technology, with the gains being bigger when technological changes have spillover effects. We therefore conclude that the ECOWAS would benefit more from trade policies aimed at shifting the technological base. JEL codes: F15, D61, O3 Key words: applied general equilibrium, trade, development, welfare, technology, ECOWAS

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All correspondence to Charles Adjasi [email protected] who is at the Department of Finance, University of Ghana, Business School, P.O Box LG78, Legon, Accra, Ghana. Emmanuel Kinful is at the Research Department, Bank of Ghana

2 I. Introduction African countries have hardly made an impact on world trade and African economies may also not be reaping a lot from trade. Yet Africa since the early 1950s has been involved in a multiplicity of trade agreements which have sought to improve the trade and economic positions of African economies. The Doha Development Agenda (DDA) is a consequence of World Trade Organization (WTO) attempts to ensure fair trade and development concerns of developing countries and aims to further open global trade across a broad front. The stalling of the talks in the Doha Round of the WTO in Geneva has however led to questions on the viability of such initiatives for developing countries, especially Africa. The Doha Rounds have sought to work around issues that address the concerns of the developing countries in the area of market access and effective participation in the international trade, as well as approach trade in a development biased manner. These have been aimed at helping address trade and development concerns of developing countries especially African economies. An important observation made by the (Stiglitz, 2000; Rodrik, 2001), is that developing countries often misunderstood commitments resulting from the Uruguay Round. In addition the lack of institutional and technical capacity hampered effective implementation.

African countries represented by the African Caribbean Pacific group (ACP) has hitherto conducted international trade under a series of arrangements with the latest being the Cotonou Partnership Agreement (CPA). With the expiry of the Cotonou Partnership Agreement (CPA) there is a newly proposed Economic Partnership Agreements (EPA) for the African Caribbean and Pacific (ACP) countries. The new partnership is supposed to create trade rather than divert trade. However it is not very clear if this new partnership will make Africa better off or worse off. Arguments and analysisboth theoretical and empirical-do not show convincing welfare benefits for African economies. A number of studies have examined the impact of EPAs on African economies and come out with conclusions showing that Africa could be a net loser especially in terms of tariff revenue loss. Tariff revenue forms an average of 7 to 10 percent of government revenue in sub-Saharan Africa.

3 In 2001, revenue from import duties as a proportion of total tax revenue was as much as 54.7% for Swaziland, 53.5% for Madagascar, 50.3% for Uganda and 49.8% for Sierra Leone (World Bank WDI 2003).How does Africa lose out here? Tariff removals accompanying the EPA will result in an erosion of these revenues and heavy losses in tariff revenue, a critical revenue source for SSA economies. A study by EUROSTEP (2004) indicated that Cameroon and Ghana will lose close to 30 percent and 20 percent respectively in government revenue from the EPA. Tekere and Ndlela (2003) also conclude on similar loses for the SADC region. Karingi et. al (2005) also show consistent revenue losses in sub-Saharan Africa (SSA) with Nigeria and Ghana being the major loses in ECOWAS, Cameroon being the largest loser in CEMAC and Angola being the largest loser in the SADC (excluding South Africa). Hinkle and Schiff, 2004 also show that EPAs offer considerable potential benefits to Sub-Sahara African (SSA) countries, but they also pose a number of policy, administrative, and institutional challenges. Some of these challenges include replacing forgone tariff revenues, avoiding serious trade diversion, appropriately regulating liberalised service industries, and liberalising internal trade. It is also argued that African economies are saddled with institutional and capacity bottlenecks which if improved can enhance Africa’s trade and development agenda. A related issue to the above is production or export capacity. African production capacity is still well below average world standards, implying that even if there was free access to the export market, production will not increase immediately. Thus what is needed immediately is an increase in capacity through technological development and input efficiency in production. Indeed the proposal by the EPAs to help increase the capacity of African export production by itself shows that in order for Africa to benefit immensely from the EPAs capacity must be improved. Technological changes have an impact on production and consumption and could also lead to changes in prices, production and consumption in related markets Frisvold (1997). Such technological changes would reduce productive and its associated institutional bottlenecks, increase capacity and productivity and thereby increase export volumes of the ECOWAS. Invariably an increased production and trade should translate into higher

4 incomes, employment and increased welfare. In our view this important area is what has been ignored in the empirics of trade and development in sub-Saharan Africa.

This paper examines the likely outcome of two trade policy scenarios in the ECOWAS region of SubSaharan Africa and the possible outcomes of an alternative policy option which influences the institutional sectors of these countries. It first explores the effects of the Doha Development Agenda on the ECOWAS economies (with representation in the GTAP data base). In addition the paper explores the effect of the EU’s EPAs being signed between the EU and African economies on these economies.

The paper also examines the possible impact of policies aimed at improving the

institutional sectors of these economies through technological change. The paper uses GTAP simulations with the standard closure assumptions and where applicable modifications such as labour market closures for unskilled labour market assumptions. The rest of the paper is organized as follows: the next section briefly discusses trade and economic structure of the ECOWAS region, section III gives an overview of trade related CGE modelling studies. The methodology applied in this paper is presented in section IV, simulations and results are discussed in section V and conclusions drawn in section VI

II. Trade and economic structure of ECOWAS The ECOWAS is comprised of 16 countries, which include: Benin, Burkina Faso, Cape Verde, Cote d’Ívoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone, and Togo. Total weighted GDP (Table 1) for the ECOWAS amounted to USD 139.3 billion in 2005. Total regional exports, including intra-regional exports, amounted to $68.4 billion in 2005, and ECOWAS registered a trade surplus of $17.5 billion in 2005. The region's major export commodities are energy products (crude oil and refined petroleum products), minerals (gold, diamonds, and bauxite) and agricultural products (cocoa, coffee, groundnuts, and cotton). Economic activity is led by three main economies, Nigeria with a GDP of USD 78 billion in 2005, Cote d’Ivoire-GDP USD16.3 billion, Ghana GDP USD10.2 billion and Senegal USD8.1 billion.

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Data from the GTAP Version 6.2 (Table 2) show that exports in the ECOWAS stood at US$ 28267 million with Nigeria’s exports making up about 60% and Ghana 10% of total ECOWAS exports. In terms of the composition of exports, exports is largely biased towards the minerals and extractive sectors-53%, agriculture-grains and crops exports constitute 11.5% and heavy manufacturing 9.3%. As expected Nigeria dominates the extractive sector of the region constituting 93% of extraction exports in the ECOWAS. Ghana also contributes 12% of grains and crop exports, 20% of transport and communications sector, 20% of heavy manufacturing sector and 13% of light manufacturing sector.

Economic activity in ECOWAS economies is hardly diversified and dominated largely by primary products: mining, agriculture, fishing and animal husbandry with the share of manufacturing being very weak. A substantial portion of ECOWAS trade-exports and imports is with the European Union, the United States and other Asian economies are however increasingly becoming involved in trade with ECOWAS. The ECOWAS region is therefore highly vulnerable to exogenous shocks such as world price fluctuations, climate and changing world trade arrangements. The ECOWAS region is yet to benefit from global trade despite efforts to integrate into the world economy. Its share in world trade remains insignificant, for instance the EU-West Africa trade flows accounted for just 1.25% of EU exports and 1.03% of EU imports in 2004.

III. Overview of trade related CGE modelling A number of studies have used CGE modelling in determining the impact of trade negotiations on various economies including those of Africa and have concluded on various issues for Africa. Achterbosch et al (2004) find that under full liberalization of global trade Sub-Saharan Africa gains about 0.3 percent of GDP. However under modest reforms, such as the Doha round, Sub-Saharan Africa losses about 2 percent of GDP, and suffers adverse terms of trade effects. Studies have also documented very large gains for liberalization of trade in services (Brown, Deardoff and Stern, 2001;

6 World Bank, 2001). These large gains have been attributed to two basic reasons. First, services make up a large proportion of consumption in most middle and high-income countries and second, services are major inputs in the production of manufactures. Hence, any trade-related reduction in the prices of services will translate into a widespread productivity gain for liberalizing economies.

Bouet et al (2004) have however also shown based on a CGE model that incorporates preference erosion, variable employment and binding overhang, that recent results of applied general equilibrium model simulations have overestimated welfare gains from trade liberalization under Doha for developing countries. Using GTAP framework Perez and Karinga (2006) estimate a welfare loss of $0.6 billion and fiscal losses from a fully implemented EPA for Africa. They also estimate trade diversion away from intra-African trade, a salient feature of the EPAs. Ackerman (2005) also shows that the gains from Doha are reducing and biased towards the developed countries rather than poverty alleviation in the developing world. Others, Fang et al. (2006) and Kwa (2006) also arrive at similar conclusions on the impact of trade liberalisation on food security and welfare on SSA. A study by McDonald and Walmsley (2003) reveals that free trade arrangements between EU and South Africa results in gains for the EU and South Africa through allocative efficiency however the rest of SubSaharan Africa loses largely in terms of allocative efficiency, employment and terms of trade. Kirkpatrick et al (2006) in a study that also examined the impact of the Doha Development Agenda, show that the economic impact of the DDA is likely to be modest and smaller than earlier predicted. Dynamic effects of the DDA show that poverty may deteriorate in SSA due to trade liberalisation losses and severe supply constraints in Africa. Indeed they argue that there is need for additional aid related policies like aid for trade’ (specific trade -related capacity-building measures) if the DDA is to be a ‘development round’.

7 IV. GTAP Methodology The model used in the simulation is the standard static GTAP model2, with perfect competition in all sectors and constant returns to scale. Regional production is generated by a constant return to scale technology in a perfectly competitive environment, and the private demand system is represented by a non-homothetic demand system (a Constant Difference Elasticity function). The foreign trade structure is characterised by the Armington (1969) assumption implying imperfect substitutability between domestic and foreign goods.

The macroeconomic closure is a neoclassical closure where investments are endogenous and adjust to accommodate any changes in savings. This approach is adopted at the global level, and investments are then allocated across regions so that all expected regional rates of return change by the same percentage. Although global investments and savings must be equal, this does not apply at the regional level, where the trade balance is endogenously determined as the difference between regional savings and regional investments. This is valid as the regional savings enter the regional utility function. The quantity of endowments (land, skilled labour and natural resources) in each region is fixed exogenously within the GTAP model.

The standard closure rules for the GTAP model were adjusted to more accurately reflect the labour markets of the African economies. There is typically an excess supply of unskilled labour in the ECOWAS and this can be tapped into by industries in the event of increased production. Thus the full employment assumption in the traditional GTAP was relaxed and the real wage rate fixed exogenously with the supply of labour endogenised to take account of the effect on unemployment.

Following Frisvold (1997), our general equilibrium approach to modelling technological changes has appealing advantages. It avoids the problem of underestimating or overestimating welfare, the constant elasticity of transformation (CET) specification of technology is appropriate as a measure of

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For a description of the GTAP model see Hertel (1997).

8 gains to production from technological advancement. A general equilibrium approach also helps examine the impact of technological changes on rewards to factor products.

As discussed earlier,

technological changes have implications for both production and consumption and ultimately welfare. In addition such changes in the innovation economy can have effects on prices, production and consumption in another market. More importantly new technology can be adopted by neighbouringother countries thus introducing spillover benefits. As explained by Frisvold (1997) and Davis (1991) such spillover benefits can be substantial. In the experiment, the structure of the model is kept simple, so that trade and other policy arrangements gains and losses emerging from simulation analysis are easy to interpret, being associated with changes in GDP and welfare.

The GTAP 5 data base is updated using GTAPAgg which uses GTAPAgAfr6 an updated GTAP with more African regions which contains 40 regions and 57 sectors. To keep the model within computational limits we have aggregated these to 10 regions and 10 sectors. These 10 regions are North America, Nigeria and the EU (25 members), Ghana, Nigeria, Rest of ECOWAS (including WAEMU) CAEMC, COMESA, SADC, COMESADC and Rest of the World.

V. Simulations and Results The first simulation examines the impact of an EPA which involves complete tariff elimination between the EU and ECOWAS. In the second simulation an EPA with the ECOWAS granting 75% tariff reduction on all EU imports whilst the EU reduces tariffs on ECOWAS imports to zero is examined. The third simulation examines the impact of the Doha Development Agenda for the ECOWAS region. This assumes 100% reduction of tariffs on imports from Sub-Saharan Africa to North America and the EU and an 80% reduction in tariffs on all imports from North America and the EU to Sub-Saharan Africa.

9 The final set of simulations is that of a technological change of 5% in the ECOWAS region. Four experiments are carried out under technological simulation. The first experiment examines the impact of an increase in output augmentation parameter ܽ‫ ݋‬for economies in the ECOWAS region simultaneously. The second experiment-falling behind technology Frisvold(1997) looks at technology change without spillovers given that Ghana and Nigeria are the most dominant economies in the region the 5% technology shock is first applied to only Ghana, and then later to only Nigeria to examine how the rest of the ECOWAS region responds. Finally the last experiment assumes technological spillovers between only Nigeria and Ghana and examines how the rest of the sub region fares. 5.1 EPA with complete tariff elimination An EPA with complete tariff elimination (Table 3) between the EU and ECOWAS results in a marginal increase in GDP to the region as a whole. Nigeria the biggest economy in the region suffers a 0.56 decline in GDP growth; however Ghana gains 1.85% growth in GDP. Note that this is the effect of zero tariffs between the EU and ECOWAS. The rest of the sub region and Nigeria suffer welfare losses from the EPAs. Welfare loses (Table 4) to the rest of ECOWAS amount to US$216.3 million and US$347.7 million for Nigeria. The only gainers of the EPAs to the sub region are Ghana and the EU itself. Ghana gains US$ 45 million whilst the EU gains a substantial US$ 1142.46 million. The welfare loses for the rest of the ECOWAS region are driven mainly by terms of trade losses and the investment savings (change in the cost of capital exports to imports) effect. In the case of Nigeria, welfare losses are driven largely by a reduction in allocative efficiency and adverse terms of trade effects. Ghana’s welfare gains appear to be driven largely by efficient utilization of resources (allocative efficiency) and endowment gains from utilizing unemployed factors of production. Contrary to the trend in all other economies, the EU gains in allocative efficiency, terms of trade effects and investment savings effect. The terms of trade effect appears to be the biggest driver of the EU’s welfare gains. Thus it appears the EPAs will help the EU enjoy from favourable terms of trade even though tariffs will be reduced. A further decomposition of the terms of trade effect (Table 5)

10 shows that the rest of ECOWAS and Nigeria loss out in all three sub components of the terms of trade effect; namely: world price effect, export price effect and import price effect. Ghana and the EU only lose out in the import price effect, with Ghana losing more US$ 0.41million than the EU US$ 0.009 million. 5.2 EPA with complete moderate tariff cuts The second simulation is based on a moderate EPA with the ECOWAS granting 75% tariff reduction on all EU imports whilst the EU reduces tariffs on ECOWAS imports to zero. Results for the GDP changes are shown in Table 6. The GDP effects are not too different from the complete tariff elimination case. GDP losses are however reduced in Nigeria to 0.15 slow down in GDP and an increase in GDP for the rest of the ECOWAS region by 0.11%, with Ghana still recording a positive GDP growth of 1.79%. Similar to the complete tariff elimination scenario welfare effects (Table 7) of the moderate EPA simulations also show welfare losses to the rest of ECOWAS to the tune of US$ 55.5 million, and US$ 81.5 million for Nigeria. Ghana and the EU again gain US$ 78.38 million and 640.81 million respectively. Again welfare losses and gains are driven primarily by allocative efficiency, terms of trade effects and investment savings effect. Further decomposition of the terms of trade effect shown in Table 8 reveals that the rest of ECOWAS suffers from adverse world price and export price effects, whilst Nigeria suffers from all three price effects. Ghana is the only partner that gains on all three price effects. 5.3 Doha Development Agenda We next examine the impact of the Doha Development Agenda for the ECOWAS region to determine if the effects would differ significantly from that of the EPAs. In this simulation we assume 100% reduction of tariffs on imports from Sub-Saharan Africa to North America and the EU and an 80% reduction in tariffs on all imports from North America and the EU to Sub-Saharan Africa. Interestingly the results (Tables 9, 10 11) again do not differ too widely from the EPA effects. The trends in GDP growth rates follow that of the moderate EPAs. Whilst welfare losses are reduced as compared to the EPA scenarios they are still significant for the rest of ECOWAS US$ 84.6million and

11 US$ 96million for Nigeria. Ghana and the EU again gain to the tune of US$ 65.54million and US$ 593.6million respectively. Welfare losses in the rest of ECOWAS come from terms of trade effects and investment savings effect. Nigeria’s welfare losses are driven mainly by losses in terms of trade and allocative efficiency. Other gainers are the CAEMC-US$ 84.2 million and COMESADC-US$ 689.7 million 5.4 Technological change Our last set of simulation exercises are based on an assumption that growth, development welfare improvement in Sub-Saharan Africa is driven by institutional changes and growth augmented by technological improvements. Hence we shock the technological parameter by 5% to examine the impacts. Results from technological shock which allows for spillovers within the ECOWAS are shown in Table 12. GDP increases substantially in the ECOWAS sub region with Ghana witnessing the highest growth rate of 13.27%. Nigeria and the rest of the ECOWAS gain 9.48% and 9.98% respectively in GPD growth. A technological change induces substantial welfare gains (Table 13) for the ECOWAS region as well. Welfare gains are higher in Nigeria-US$ 3933.5 million and US$ 2959.8 million for the rest of the sub region. Most importantly allocative efficiency drives welfare changes. In addition the endowment effects show the increased and efficient utilization of unemployed factors of production-in this case unskilled labour. This is further evidenced in the table on returns to factors of production in Table 14. Returns to unskilled labour in the ECOWAS region are greater than that of all other factors of production. Returns to unskilled labour is highest in Nigeria US$ 474. We next assume technological shocks without spillovers. First we run simulations with shocks to only Ghana, and then subsequently shocks to only Nigeria and finally joint shocks to Ghana and Nigeria without spillovers to the rest of ECOWAS (Tables 15 to 20). A technological shock to Ghana alone induces growth in GDP but reduces welfare in Nigeria. Subsequent technology simulations produce growth in GDP and welfare gains in the ECOWAS region with no losers. However GDP growth and welfare gains are marginal when compared to technological shocks with spillovers. On the whole, it

12 appears that in terms of growth and welfare, the ECOWAS region would benefit significantly and much more from a 5% technological improvement than the EPA and DDA trade arrangements.

VI. Conclusion This paper uses GTAP’s applied general equilibrium model to examine the impact of EPAs; DDA on growth and welfare in ECOWAS in Africa. It also examines the effect of a technological change in ECOWAS to examine whether technology developments are more important in driving growth and welfare. The results show that an EPA arrangement with a complete tariff reduction results in welfare losses to Nigeria- US$347.7 million and the rest of ECOWAS S$216.3 with gains only to Ghana and the EU. An EPA with moderate tariff cuts also yields losses to the rest of ECOWAS to the tune of US$ 55.5 million, and US$ 81.5 million for Nigeria. In all the welfare loses for the rest of the ECOWAS region are driven mainly by terms of trade losses-world price effect, export price effect and import price effect-and the investment savings (change in the cost of capital exports to imports) effect. Ghana’s welfare gains appear to be driven largely by efficient utilization of resources (allocative efficiency) and endowment gains from utilizing unemployed factors of production. The terms of trade effect appears to be the biggest driver of the EU’s welfare gains. Simulations based on the Doha Development Agenda for the ECOWAS region show effects that do not vary widely from the EPA effects. The trends in GDP growth rates follow that of the moderate EPAs. There are still welfare losses of US$ 84.6million to the rest of ECOWAS and US$ 96million for Nigeria. Ghana and the EU again gain to the tune of US$ 65.54million and US$ 593.6million respectively. It therefore appears that in terms of GDP and welfare gains, the EPAs and the DDA arrangements may be beneficial only to the EU and Ghana. Other economies within the ECOWAS region stand to lose out on such arrangements. Without going further to examine sectoral effects of the EPAs and DDA, it is clear from decomposing the welfare impacts that the arrangements as they stand have adverse terms of trade effects which divert trade rather than create trade. More so these adverse effects are strong enough to override any favourable gains to be made from these

13 arrangements. Unlike the EU economies, the economies in the ECOWAS are not able to take advantage of the EPAs and other trade and development agendas like the DDA. Finally as an alternative or advice to the EPA, DDA or any other trade related development policy, we propose a policy that aims mostly at increasing the output augmenting base of economies in the ECOWAS region and or other parts of sub-Saharan Africa. We therefore run simulations which increase technology by 5% in the ECOWAS. A technological change induces substantial welfare gains for the ECOWAS region. Welfare gains are higher in Nigeria-US$ 3933.5 million and US$ 2959.8 million for the rest of the sub region. An important issue here is the fact that welfare changes are driven to a significant extent by allocative efficiency. Thus there is improved efficiency in utilization of resources in production. In addition the endowment effects show an increased and efficient utilization of unemployed factors of production in the ECOWAS region. Indeed returns to unskilled labour in the ECOWAS are greater than that of all other factors of production. Note here that there is substantial supply of labour (unemployment) especially unskilled labour in the sub region. On the whole, it appears that in terms of growth and welfare, the ECOWAS region would benefit significantly and much more from a 5% technological improvement than the EPA and DDA trade arrangements. Therefore in addition to the need for fair trade and elimination of tariffs and subsidies in global development, in the case of a trade and development agenda for less developed economies it may be more prudent for trade and development arrangements to aim largely at helping increase technological base rather than just focusing on tariff arrangements.

14 References Achterbosch T., Ben Hammouda, H., Osakwe, P. N., and van Tongeren, F. W. 2004. Trade Liberalization under the Doha Development Agenda: Options and Consequences for Africa. The Hague: Agricultural Economics Research Institute ( EI).

Armington, P.S.1969. ‘A Theory of Demand for Products Distinguished by Place of Production’, IMF Staff Papers, Vol 16, pp 159-178.

Bouet A., Bureau J.C., Decreux Y., Jean S., 2004, Multilateral Agricultural Trade Liberalization: The Contrasting Fortunes of Developing Countries in the Doha Round CEPII Working Paper N° 200418, November 2004

Brown, D. K., A. V. Deardorff and R. M. Stern. 2001. “CGE Modelling and Analysis of Multilateral and Regional Negotiation Options”, Research Seminar in International Economics, Discussion Paper No. 468.

Davis, J. 1991 Spillover effects of agricultural research: Importance for research policy and incorporation in research evaluation models, ACIAR/ISNAR Project Papers No. 32

EUROSTEP. 2004 “New ACP-EU Trade Arrangements: New Barriers to Eradicating Poverty?” EUROSTEP, Brussels, Belgium.

Fang, Cheng, Jian Zhang and BenBelhassen, B. 2006. The Impact of Multilateral Trade Liberalization on Food Security in Sub-Saharan Africa and South Asia. Paper presented at 9th Annual GTAP Conference, Addis Ababa, Ethiopia, June 2006.

15 Firsvold George, B. 1997. Multimarket effects of agricultural research with technological spillovers in Thomas W. Hertel ed. Global Trade Analysis: Modeling and Applications, pp321-346 Cambridge University Press

Hinkle, Lawrence and Maurice Schiff 2004. Economic Partnership Agreements between sub-Saharan Africa and the EU: A development perspective, The World Economy Vol 27(9) 1321-33 Karingi, S., R. Lang, N. Oulmane, R. Perez, M. S. Jallab and H. B. Hammonda. 2005. “Economic and Welfare Impacts of the EU-Africa Economic Partnership Agreements” African Trade Policy Centre Working paper No. 10 Economic Commission for Africa ECA, Addis Ababa. Kirkpatrick, C., George, C. and Scrieciu, S. 2006. Sustainability Impact Assessment of Proposed WTO Negotiations’, Institute for Development policy and Management. University of Manchester, May 2006.

Kwa, A. 2006. Recent Assessments: Africa To Lose Out From WTO Negotiations, Even In Agriculture. Focus on Global South, June 2006.

McDonald, Scott and Terrie L. Walmsley 2003 Bilateral Free Trade Agreements and Customs Unions: The Impact of the EU Republic of South Africa Free Trade Agreement on Botswana1 GTAP Working Paper No. 29

Perez, R. and Njuguna Karingi, S. 2006. Will the Economic Partnership Agreements foster the Sub-Saharan African Development?, United Nations Economic Commission for Africa, 2006.

Rodrik, D. (2001), “The Global Governance of Trade as if Development Really Mattered”, report prepare for the UNDP, mimeo.

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Stiglitz, J. E. 2000. “Two Principles for the Next Round or, How to Bring Developing Countries in from the Cold”, The World Economy, 23, No. 4, 437-453. Tekere, M. And D. Ndlela. 2003. “Impact Assessment of EPAs on Southern African Development Commission and Preliminary Adjustment Scenarios” Final Report, Trade and Development Studies Centre, Harare, Zimbabwe World Bank 2003 World Development Indicators World Bank, (2001), Global Economic Prospects and the Developing Countries, The World Bank, Washington D.C

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Tables Table 1 Economic growth ECOWAS 2005

Country

Gross

Real GDP

Domestic

Growth

Product

Rate,

2005 (Billions of U.S. $) Benin

$4.3

4.8

Burkina Faso

$5.2

3.5

Cape Verde

$1.1

5.9

Cote d’Ivoire

$16.3

1.1

Gambia

$0.5

4.5

Ghana

$10.2

5.7

Guinea

$3.0

3

Guinea-Bissau

$0.3

2.3

Liberia

$0.5

7.5

Mali

$5.3

5.8

Niger

$3.3

3.5

Nigeria

$78.0

5.9

Senegal

$8.1

5.8

Sierra Leone

$1.1

6.9

Togo

$2.1

2.8

$139.3

5

Regional Total/Weighted Average Source: Global Insight

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Table 2 Value of Merchandised Exports FOB

VXMD

Ghana

Commodities

USD

Nigeria %

%ECOWAS

millions

USD

RECOWAS

ECOWAS

%

%ECOWAS

USD millions

%

USD millions

%

millions

Grains & Crops

394.82

0.20

0.12

271.39

0.02

0.08

2577.43

0.25

3243.64

0.11

Livestock & Meat

8.86

0.00

0.08

9.05

0.00

0.09

88.07

0.01

105.98

0.00

Extraction

80.03

0.04

0.01

14100.91

0.88

0.93

924.56

0.09

15105.50

0.53

Processed Food

244.73

0.12

0.17

154.38

0.01

0.10

1077.92

0.11

1477.04

0.05

Textiles & Cloth

16.57

0.01

0.09

23.58

0.00

0.13

145.74

0.01

185.88

0.01

Light Manufacture

283.23

0.14

0.13

184.82

0.01

0.09

1703.27

0.17

2171.32

0.08

Heavy Manufacture

512.04

0.26

0.20

221.75

0.01

0.08

1884.46

0.18

2618.24

0.09

Utilities & Construction

31.43

0.02

0.08

199.92

0.01

0.54

141.58

0.01

372.93

0.01

Transport & Comm.

274.82

0.14

0.20

330.25

0.02

0.24

779.53

0.08

1384.61

0.05

Other Services

117.03

0.06

0.07

606.04

0.04

0.38

879.10

0.09

1602.17

0.06

Total

1963.57

1.00

0.07

16102.10

1.00

0.57

10201.65

1.00

28267.33

1.00

Source: authors’ computation from GTAP Data base

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Table 3 GDP Effects-Complete tariff reduction EPA

Region

Simulated GDP change

North America

0

EU_25

0

Ghana

1.85

Nigeria

-0.56

Rest ECOWAS

0

CAEMC

-0.01

COMESA

0

SADC

0

COMESADC

0

Rest of World

0

Source: authors’ computation from GTAP simulations

Table 4 Welfare effects of EPA complete tariff cuts

Region

Allocative

Endowment

Terms of trade

Investment

Total Welfare

Efficiency

Effect

effect

Savings effect

North America

-38.606

0

-53.004

-39.385

-130.995

EU

121.873

0

1012.803

7.789

1142.466

Ghana

64.084

33.542

-10.804

-41.777

45.045

Nigeria

-280.887

50.937

-184.111

66.334

-347.728

Rest ECOWAS

0.641

0

-104.332

-112.662

-216.353

CAEMC

-1.245

0

-5.007

0.876

-5.376

COMESA

-0.475

0

-1.796

-0.821

-3.091

20 SADC

-5.296

0

-26.613

5.512

-26.397

COMESADC

0.315

0

-3.086

0.179

-2.592

Rest of World

-78.889

0

-628.573

114.854

-592.608

Total

-218.487

84.479

-4.523

0.901

-137.63


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Table 5 Terms of Trade Decomposition of EPA complete tariff cut

Terms of trade

North

EU

Ghana

Nigeria

Rest

CAEMC

COMESA

SADC

COMESADC

components

America

world price

0.002

0.002

0.003

-0.058

-0.001

-0.044

-0.006

-0.002

-0.021

-0.003

-0.127

export price

-0.019

0.043

0.164

-0.558

-0.196

-0.028

-0.028

-0.068

-0.015

-0.027

-0.733

import price

0.01

-0.009

-0.41

-0.519

-0.495

0.01

0.01

0.02

0.017

0.009

-1.356

Total

-0.007

0.036

-0.244

-1.135

-0.691

-0.062

-0.023

-0.05

-0.02

-0.02

-2.216

ECOWAS


Rest of

Total

World

22

Table 6 GDP effect of moderate EPA

Region


North America

0

EU

0

Ghana

1.79

Nigeria

-0.15

Rest ECOWAS

0.11

CAEMC

0

COMESA

0

SADC

0

COMESADC

0

Rest of World

0


Table 7 Welfare effect of moderate EPA

Region

North America

Allocative

Endowment

Terms of

Investment

Allocative

Total

Efficiency

Effect

trade

Savings

Efficiency

Welfare

effect

effect

-28.033

0

-51.793

-26.39

0

-106.217

EU

22.513

0

614.145

4.159

0

640.818

Ghana

68.074

26.62

9.165

-25.475

0

78.384

-106.279

45.652

-68.039

47.11

0

-81.556

Rest ECOWAS

34.418

0

-9.029

-80.929

0

-55.54

CAEMC

-0.968

0

-3.601

0.643

0

-3.926

Nigeria

23 COMESA

-0.41

0

-1.663

-0.627

0

-2.7

-4.213

0

-20.909

4.058

0

-21.064

COMESADC

0.24

0

-2.276

0.124

0

-1.912

Rest of World

-62.168

0

-467.213

77.701

0

-451.68

Total

-76.826

72.272

-1.212

0.372

0

-5.394

SADC


24 Table 8 Terms of Trade decomposition of moderate EPA

Terms of

North

trade

America

EU

Ghana

Nigeria

Rest

CAEMC

COMESA

SADC

COMESADC

ECOWAS

Rest of

Total

World

components world price

0.001

0.002

0.001

-0.038

-0.003

-0.028

-0.006

-0.002

-0.015

-0.002

-0.089

export price

-0.013

0.029

0.346

-0.365

-0.107

-0.021

-0.019

-0.05

-0.009

-0.019

-0.228

import price

0.007

-0.009

0.049

-0.006

0.016

0.004

0.005

0.012

0.01

0.005

0.093

Total price

-0.006

0.022

0.396

-0.409

-0.093

-0.045

-0.02

-0.04

-0.015

-0.015

-0.224


25 Table 9 GDP effects of DDA

Region


North America

0

EU

0.01

Ghana

1.9

Nigeria

-0.18

Rest ECOWAS

0.13

CAEMC

0.21

COMESA

0

SADC

-0.01

COMESADC

0.09

Rest of World

0


Table 10 Welfare Effects of DDA

Region

Allocative

Endowment

Terms of

Investment

Total

Efficiency

Effect

trade

Savings

Welfare

effect

effect

North America

17.752

0

5.584

-37.425

-14.089

EU

475.738

0

127.861

-9.931

593.668

Ghana

75.649

24.665

0.171

-34.945

65.54

Nigeria

-122.935

47.497

-77.143

56.566

-96.015

Rest ECOWAS

39.246

0

-24.502

-99.411

-84.667

CAEMC

42.882

0

-5.539

46.94

84.283

COMESA

-0.173

0

-6.542

-1.333

-8.048

SADC

-11.864

0

-36.298

2.648

-45.514

COMESADC

34.218

0

663.157

-7.67

689.705

26 Rest of World

-126.532

0

-663.418


85.369

-704.581

27

Table 11 Terms of Trade Decomposition of DDA

Terms of

North

Trade

America

EU

Ghana

Nigeria

Rest

CAEMC

COMESA

SADC

COMESADC

ECOWAS

Rest of

Total

World

Components world price

0.001

0

0.01

-0.015

0.014

-0.005

0.01

0.001

0.005

-0.001

0.02

export price

-0.008

0.016

-0.089

-0.452

-0.307

-0.052

-0.057

-0.034

4.448

-0.03

3.434

import price

0.006

-0.011

0.059

0.008

0.043

-0.013

-0.015

-0.052

-0.108

0.009

-0.074

world price

-0.001

0.005

-0.019

-0.459

-0.251

-0.07

-0.062

-0.084

4.344

-0.022

3.38


28 Table 12 GDP Effects of ECOWAS technology shock with spillovers

Region

Simulated GDP changes

North America

0

EU

0

Ghana

13.27

Nigeria

9.48

Rest ECOWAS

9.98

CAEMC

0

COMESA

0

SADC

0

COMESADC

0

Rest of World

0


Table 13 Welfare effects of ECOWAS technology shock with spillovers

Region

Allocative

Endowment

Terms of

Investment

Allocative

Total

Efficiency

Effect

trade

Savings

Efficiency

Welfare

effect

effect

North America

-51.621

0

0

-90.796

31.518

-110.9

EU

-71.003

0

0

24.758

59.318

13.072

Ghana

162.064

73.754

465.663

71.127

-21.632

750.977

Nigeria

391.543

263.845

3255.737

-52.898

75.322

3933.549

Rest ECOWAS

423.995

0

2672.757

148.529

-285.446

2959.834

CAEMC

-0.233

0

0

-1.657

0.198

-1.692

COMESA

-0.171

0

0

0.378

0.222

0.429

SADC

0.331

0

0

4.102

-0.176

4.257

COMESADC

-0.367

0

0

-1.488

0.194

-1.661

29 Rest of World

-57.615

0

0

-106.448

146.765

-17.298

Total

796.922

337.599

6394.157

-4.393

6.283

7530.568


30 Table 14 Rewards to factors of production of ECOWAS technology shock (spillovers)

Factors

North America

EU

Ghana

Nigeria

Rest ECOWAS

CAEMC

COMESA

SADC

COMESADC

Rest of World

Total

Land

-100.169

-143.329

10.334

9.572

5.069

3.877

6.088

7.154

3.898

-3.442

-200.949

Unskilled Lab

312.914

760.983

157.653

474.152

105.684

95.475

72.064

52.657

43.149

166.779

2241.509

Skilled Lab

307.971

761.86

52.871

49.063

111.107

100.153

81.752

52.991

43.931

219.459

1781.158

Capital

43.35

-47.672

52.871

49.064

28.156

20.362

36.455

33.004

25.085

23.483

264.158

Natural Res

6.339

4.467

5.287

4.906

3.165

2.869

4.236

3.448

4.073

2.943

41.734

Total

570.404

1336.308

279.016

586.758

253.181

222.737

200.595

149.254

120.135

409.221

4127.609


31 Table 15 GDP effect of technology shock to Ghana (no spillovers)

Region


North America

0

EU

0

Ghana

13.23

Nigeria

0

Rest ECOWAS

0.01

CAEMC

0

COMESA

0

SADC

0

COMESADC

0

Rest of World

0


Table 16 Welfare effects of technology shock to Ghana (no spillovers)

Region

Allocative

Endowment

Terms of

Investment

Allocative

Total

Efficiency

Effect

trade

Savings

Efficiency

Welfare

effect

effect

North America

-12.905

0

0

-25.852

-4.096

-42.853

EU

-16.111

0

0

-19.292

5.953

-29.449

Ghana

161.101

72.882

465.41

68.507

-22.808

745.093

-1.288

0.083

0

0.004

-0.147

-1.348

4.394

0

0

4.082

3.058

11.534

CAEMC

-0.069

0

0

0.009

0.022

-0.038

COMESA

-0.047

0

0

0.118

0.033

0.103

0.32

0

0

1.511

-0.498

1.333

Nigeria Rest ECOWAS

SADC

32 COMESADC

-0.093

0

0

0.275

0.002

0.184

Rest of World

-16.097

0

0

-30.804

19.092

-27.809

Total

119.205

72.966

465.41

-1.441

0.611

656.751


33 Table 17 GDP effect of technology shock to Nigeria (no spillovers)

Region


North America

0

EU

0

Ghana

0

Nigeria

0.02

Rest ECOWAS

9.47

CAEMC

0

COMESA

0

SADC

0

COMESADC

0

Rest of World

0


Table 18 Welfare effects of technology shock to Nigeria (no spillovers)

Region

North America

Allocative

Endowment

Terms of

Investment

Allocative

Total

Efficiency

Effect

trade

Savings

Efficiency

Welfare

effect

effect

-4.209

0

0

5.72

-14.341

-12.829

EU

1.014

0

0

72.706

-16.916

56.804

Ghana

0.825

0.182

0

2.116

0.222

3.345

392.206

262.57

3255.581

-53.444

74.659

3931.572

Rest ECOWAS

0.769

0

0

0.815

0.045

1.63

CAEMC

-0.14

0

0

-2.03

0.063

-2.107

COMESA

0.009

0

0

-0.719

-0.048

-0.758

SADC

0.619

0

0

2.136

-0.743

2.012

COMESADC

-0.07

0

0

-2.271

-0.036

-2.377

Nigeria

34 Rest of World Total

9.896

0

0

-25.498

-42.333

-57.936

400.92

262.752

3255.581

-0.469

0.572

3919.356


35 Table 19 GDP effect of technology shock to Ghana and Nigeria simultaneously (no spillovers to rest of ECOWAS)

Region


EU

0

Ghana

0

Nigeria

13.25

Rest ECOWAS

9.47

CAEMC

0.02

COMESA

0

SADC

0

COMESADC

0

Rest of World

0

EU

0


Table 20 Welfare effect of technology shock to Ghana and Nigeria simultaneously (no spillovers to rest of ECOWAS)

Region

Allocative

Endowment

Terms of

Investment

Allocative

Total

Efficiency

Effect

trade

Savings

Efficiency

Welfare

effect

effect

North America

-17.089

0

0

-20.124

-18.425

-55.639

EU

-15.087

0

0

53.417

-10.967

27.362

Ghana

161.837

73.07

465.54

70.529

-22.595

748.381

Nigeria

390.934

262.672

3255.675

-53.487

74.522

3930.315

5.154

0

0

4.887

3.095

13.137

CAEMC

-0.208

0

0

-2.019

0.084

-2.142

COMESA

-0.038

0

0

-0.6

-0.015

-0.654

Rest ECOWAS

36 SADC

0.937

0

0

3.641

-1.239

3.339

COMESADC

-0.163

0

0

-1.995

-0.034

-2.191

Rest of World

-6.19

0

0

-56.201

-23.253

-85.644

520.087

335.742

3721.215

-1.953

1.172

4576.263

Total
